Print a naivedensityratio object

Print a naivedensityratio object

Usage

# S3 method for class 'naivedensityratio'
print(x, digits = max(3L, getOption("digits") - 3L), ...)

Arguments

x

Object of class naivesubspacedensityratio.

digits

Number of digits to use when printing the output.

...

further arguments on how to format the number of digits.

Value

invisble The inputted naivedensityratio object.

See also

print, naive

Examples

set.seed(123)
# Fit model
dr <- naive(numerator_small, denominator_small)
# Inspect model object
dr
#> 
#> Call:
#> naive(df_numerator = numerator_small, df_denominator = denominator_small)
#> 
#> Naive density ratio
#>   Number of variables: 3
#>   Number of numerator samples: 50
#>   Number of denominator samples: 100
#>   Numerator density: num [1:50] 1.41 5.74 1.87 4.13 1.67 ...
#>   Denominator density: num [1:100] 2.93 0.071 1.065 1.59 2.115 ...
#>  
# Obtain summary of model object
summary(dr)
#> 
#> Call:
#> naive(df_numerator = numerator_small, df_denominator = denominator_small)
#> 
#> Naive density ratio estimate:
#>   Number of variables: 
#>   Number of numerator samples: 50
#>   Number of denominator samples: 100
#>   Density ratio for numerator samples: num [1:50] 0.344 1.747 0.628 1.419 0.511 ...
#>   Density ratio for denominator samples: num [1:100] 1.0751 -2.6454 0.0626 0.464 0.7493 ...
#>  
#> 
#> Squared average log density ratio difference for numerator and denominator samples (SALDRD): 13.56
#> For a two-sample homogeneity test, use 'summary(x, test = TRUE)'.
#> 
# Plot model object
plot(dr)
#> Warning: Negative estimated density ratios for 25 observation(s) converted to 0.01 before applying logarithmic transformation
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

# Plot density ratio for each variable individually
plot_univariate(dr)
#> Warning: Negative estimated density ratios for 25 observation(s) converted to 0.01 before applying logarithmic transformation
#> [[1]]

#> 
#> [[2]]

#> 
#> [[3]]

#> 
# Plot density ratio for each pair of variables
plot_bivariate(dr)
#> Warning: Negative estimated density ratios for 25 observation(s) converted to 0.01 before applying logarithmic transformation
#> [[1]]

#> 
#> [[2]]

#> 
#> [[3]]

#> 
# Predict density ratio and inspect first 6 predictions
head(predict(dr))
#> [1] 1.410607 5.739287 1.874031 4.131255 1.666760 4.095855
# Fit model with custom parameters
naive(numerator_small, denominator_small, m=2, kernel="epanechnikov")
#> 
#> Call:
#> naive(df_numerator = numerator_small, df_denominator = denominator_small,     m = 2, kernel = "epanechnikov")
#> 
#> Naive density ratio
#>   Number of variables: 3
#>   Number of numerator samples: 50
#>   Number of denominator samples: 100
#>   Numerator density: num [1:50] 0.572 1.421 0.945 1.058 0.936 ...
#>   Denominator density: num [1:100] 1.391 1.459 0.572 0.943 1.314 ...
#>